jkestelyn
Joined 14 years ago
Joined 14 years ago
[Disclaimer: I work on the Chatbase team]
You'd think from this article that deploying a bot is like letting a dog off its leash and you just have to hope that it doesn't bite anyone. In fact there are several common-sense ways to prevent a bot from going rogue, including monitoring how it responds to intents and then making changes as needed.
Exactly; if you build a bot with the intention of relying 100% on NLP, you're asking for trouble. But I fail to see how that fact leads to chatbots being useless when there are plenty of tools available for guiding necessary optimizations that can lead to a much better experience.
When websites were bad we turned to tools like Google Analytics to make website development data driven -- we didn't stop building them.
Those flaws derive from a wildly optimistic use case for the technology, though. A much cleaner use case would have been a bot intended for Facebook Help (instead of, or to complement, a KB -- assuming people still need that).
More ambitious maybe, but perhaps not impossible, would be a bot that looks for signs of suicidal tendencies in posts or comments and engages the user in therapeutic conversation. (?)
1. When reasonably scoped (i.e., to a specific use case) and iteratively optimized over time, chatbots can meet user expectations quite well.
2. If ostensibly intended by their builders to handle every type of request on the fly via ML pixie dust, chatbots can be miserable failures.
Both things can be equally true.
(Disclaimer: I work for Chatbase, a service for analyzing and optimizing bots. Maybe Facebook should have looked at that. :) )